Machine Learning Infrastructure Site Reliability Engineer

Apple India Pvt Ltd; Bengaluru; On-site; INR 2,500,000 - 4,000,000; Full time

Job summary

Apple India Pvt Ltd in Bengaluru seeks an experienced Site Reliability Engineer for the ML Infrastructure team. You will help manage Apple's largest ML compute platform, ensuring high availability and scalable performance across cloud environments.

The role emphasizes Kubernetes, automation, and collaboration; you will own designs end-to-end, implement robust monitoring, and contribute to a culture of continuous improvement.

Qualifications

• 3+ years building and scaling large applications in cloud environments.
• Deep expertise in Kubernetes with hands-on experience in GKE or EKS.
• Proficient in Python, Go, or Rust.
• Experience with object storage (S3-compatible or Google Cloud Storage).
• Strong networking and Linux internals knowledge.

Responsibilities

• Design, deploy, and operate ML compute infrastructure at scale.
• Automate operations and drive reliability via IaC and CI/CD.
• Collaborate across teams to align technical direction and deliverables.
• Troubleshoot complex performance and availability issues.

Skills

Kubernetes

Python

Go

Rust

Linux

Networking

Tools

Spinnaker

Helm

Flux

GKE

EKS

Job description

ML Infrastructure Service Reliability Engineer- Apple Services Engineering Summary

At Apple, we don't just build products - we create transformative experiences that have reshaped entire industries. Our innovation is driven by the diversity of our people and their ideas, inspiring everything we do. Imagine the impact you could make. Join Apple and help us leave the world better than we found it. The ML Infrastructure team is responsible for managing Apple's largest ML compute platform, multi-cloud storage abstraction and caching platform, which supports critical machine learning training workloads that power user-facing features across the Apple ecosystem. Operating across both first-party and third-party cloud environments brings complex and unique challenges. As a Site Reliability Engineer (SRE) on the ML Infrastructure team, you'll be expected to address these challenges through a strong foundation in cloud object storage, data analysis, automation, collaboration, and advanced expertise in Kubernetes. Our team oversees the full infrastructure stack - from low-level nodes to the complete network architecture - ensuring our platform remains highly available, resilient, and efficient at scale.

Description

We are seeking an experienced Software and Systems Engineer to join our dynamic team. This role demands a proactive mindset, technical excellence, and a collaborative spirit.

The ideal candidate will demonstrate

• Strong critical thinking and a high degree of individual accountability.
• Effective communication and collaboration skills.
• A genuine passion for Infrastructure as a Service (IaaS).
• A commitment to automation and operational efficiency.
• Ownership of projects from design through delivery.
• A solutions-oriented approach, coupled with the ability to gain alignment on technical direction.
• Consistent and timely execution of design implementations aligned with project objectives.
• The ability to provide constructive technical feedback, fostering team-wide growth and continuous improvement.

Preferred Qualifications

• Proven drive to automate manual operations and enhance processes through continuous iteration.
• Strong understanding of best practices for deploying large-scale, distributed applications.
• Hands-on experience managing diverse system environments using configuration management tools or software delivery platforms such as Spinnaker, Helm, or Flux.
• Demonstrated expertise in deploying, supporting, and monitoring both new and existing services, platforms, and application stacks.
• Solid familiarity with container orchestration and management using Kubernetes.

Minimum Qualifications

• 3+ years experience in building, operating and scaling a large application in a private, public or hybrid cloud environment.
• Deep expertise in Kubernetes, with hands-on experience using platforms such as Google Kubernetes Engine (GKE) or Amazon Elastic Kubernetes Service (EKS).
• Proficient in designing, developing, and releasing code in languages such as Python, Go, or Rust.
• Practical experience with object storage technologies, including Amazon S3 or Google Cloud Storage (GCS).
• Strong background in designing and troubleshooting complex networking issues in both public and private cloud infrastructures.
• Solid understanding of Linux internals, standard networking protocols, and distributed systems architecture.